Chapter 5 Community composition
5.1 Taxonomy overview
5.1.1 Stacked barplot
genome_counts_filt %>%
mutate_at(vars(-genome),~./sum(.)) %>% #apply TSS nornalisation
pivot_longer(-genome, names_to = "sample", values_to = "count") %>% #reduce to minimum number of columns
left_join(., genome_metadata, by = join_by(genome == genome)) %>% #append genome metadata
left_join(., sample_metadata, by = join_by(sample == sample)) %>% #append sample metadata
filter(count > 0) %>% #filter 0 counts
ggplot(., aes(x=sample,y=count, fill=phylum, group=phylum)) + #grouping enables keeping the same sorting of taxonomic units
geom_bar(stat="identity", colour="white", linewidth=0.1) + #plot stacked bars with white borders
scale_fill_manual(values=phylum_colors) +
facet_nested(. ~ altitude + treatment, scales="free") + #facet per day and treatment
guides(fill = guide_legend(ncol = 1)) +
theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1),
axis.title.x = element_blank(),
panel.background = element_blank(),
panel.border = element_blank(),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
axis.line = element_line(linewidth = 0.5, linetype = "solid", colour = "black")) +
labs(fill="Phylum",y = "Relative abundance",x="Samples")Number of bacteria phyla
[1] 13
5.1.2 Phylum relative abundances
phylum_summary <- genome_counts_filt %>%
mutate_at(vars(-genome),~./sum(.)) %>% #apply TSS nornalisation
pivot_longer(-genome, names_to = "sample", values_to = "count") %>%
left_join(sample_metadata, by = join_by(sample == sample)) %>%
left_join(genome_metadata, by = join_by(genome == genome)) %>%
group_by(sample,phylum,region, environment,treatment) %>%
summarise(relabun=sum(count))phylum_summary %>%
group_by(phylum) %>%
summarise(total_mean=mean(relabun*100, na.rm=T),
total_sd=sd(relabun*100, na.rm=T)) %>%
mutate(total=str_c(round(total_mean,2),"±",round(total_sd,2))) %>%
arrange(-total_mean) %>%
dplyr::select(phylum,total) %>%
tt()| phylum | total |
|---|---|
| p__Bacteroidota | 56.02±16.86 |
| p__Bacillota_A | 17.72±6.39 |
| p__Pseudomonadota | 11.57±13.5 |
| p__Bacillota | 5.48±8.81 |
| p__Verrucomicrobiota | 4.12±4.51 |
| p__Desulfobacterota | 1.79±1.74 |
| p__Fusobacteriota | 1.37±2.18 |
| p__Bacillota_C | 0.65±0.93 |
| p__Deferribacterota | 0.6±0.77 |
| p__Cyanobacteriota | 0.37±0.5 |
| p__Bacillota_B | 0.15±0.14 |
| p__Elusimicrobiota | 0.13±0.43 |
| p__Chlamydiota | 0.03±0.08 |
phylum_arrange <- phylum_summary %>%
group_by(phylum) %>%
summarise(mean=mean(relabun)) %>%
arrange(-mean) %>%
select(phylum) %>%
pull()
phylum_summary %>%
filter(phylum %in% phylum_arrange) %>%
mutate(phylum=factor(phylum,levels=rev(phylum_arrange))) %>%
ggplot(aes(x=relabun, y=phylum, group=phylum, color=phylum)) +
scale_color_manual(values=phylum_colors[rev(phylum_arrange)]) +
geom_jitter(alpha=0.5) +
theme_minimal() +
theme(legend.position="none") +
labs(y="Phylum",x="Relative abundance")5.2 Taxonomy boxplot
5.2.1 Family
family_summary <- genome_counts_filt %>%
mutate_at(vars(-genome),~./sum(.)) %>% #apply TSS nornalisation
pivot_longer(-genome, names_to = "sample", values_to = "count") %>% #reduce to minimum number of columns
left_join(sample_metadata, by = join_by(sample == sample)) %>% #append sample metadata
left_join(., genome_metadata, by = join_by(genome == genome)) %>% #append genome metadata
group_by(sample,family) %>%
summarise(relabun=sum(count))
family_summary %>%
group_by(family) %>%
summarise(mean=mean(relabun, na.rm=T),sd=sd(relabun, na.rm=T)) %>%
arrange(-mean) %>%
tt()| family | mean | sd |
|---|---|---|
| f__Bacteroidaceae | 2.747168e-01 | 1.407196e-01 |
| f__Rikenellaceae | 1.391991e-01 | 7.396770e-02 |
| f__Tannerellaceae | 7.720647e-02 | 4.561100e-02 |
| f__Ruminococcaceae | 5.793749e-02 | 4.189494e-02 |
| f__Lachnospiraceae | 4.729335e-02 | 3.337791e-02 |
| f__Enterobacteriaceae | 4.336104e-02 | 9.482159e-02 |
| f__Akkermansiaceae | 3.968436e-02 | 4.368196e-02 |
| f__Marinifilaceae | 3.738796e-02 | 3.555050e-02 |
| f__Aeromonadaceae | 3.216280e-02 | 5.116161e-02 |
| f__Mycoplasmoidaceae | 3.122255e-02 | 8.895328e-02 |
| f__Erysipelotrichaceae | 2.221957e-02 | 1.788968e-02 |
| f__ | 1.956762e-02 | 1.924658e-02 |
| f__Desulfovibrionaceae | 1.794839e-02 | 1.740772e-02 |
| f__Fusobacteriaceae | 1.368885e-02 | 2.180794e-02 |
| f__Clostridiaceae | 1.366840e-02 | 1.906657e-02 |
| f__Moraxellaceae | 1.342615e-02 | 2.724203e-02 |
| f__Oscillospiraceae | 1.250406e-02 | 8.936335e-03 |
| f__Cellulosilyticaceae | 1.133545e-02 | 2.080456e-02 |
| f__Butyricicoccaceae | 9.655203e-03 | 2.753799e-02 |
| f__CAG-239 | 8.744086e-03 | 1.388356e-02 |
| f__CHK158-818 | 7.109525e-03 | 8.651652e-03 |
| f__Anaerovoracaceae | 6.170476e-03 | 9.224529e-03 |
| f__Mucispirillaceae | 6.016547e-03 | 7.689861e-03 |
| f__Peptostreptococcaceae | 5.928800e-03 | 1.660295e-02 |
| f__P3 | 5.211451e-03 | 8.758697e-03 |
| f__Muribaculaceae | 5.091676e-03 | 6.107022e-03 |
| f__UBA3637 | 5.049775e-03 | 1.024626e-02 |
| f__Gastranaerophilaceae | 3.475214e-03 | 4.812600e-03 |
| f__Anaerotignaceae | 2.499790e-03 | 2.422026e-03 |
| f__UBA932 | 2.488889e-03 | 4.069053e-03 |
| f__Acutalibacteraceae | 2.311710e-03 | 3.337834e-03 |
| f__Chromobacteriaceae | 2.083279e-03 | 9.013217e-03 |
| f__UBA3830 | 2.074625e-03 | 3.362372e-03 |
| f__Pumilibacteraceae | 2.041528e-03 | 2.464352e-03 |
| f__Massilibacillaceae | 1.915668e-03 | 3.861941e-03 |
| f__Succinispiraceae | 1.875117e-03 | 2.130021e-03 |
| f__UBA1997 | 1.620725e-03 | 4.440974e-03 |
| f__Chitinibacteraceae | 1.502709e-03 | 3.412014e-03 |
| f__Pseudomonadaceae | 1.420060e-03 | 2.808340e-03 |
| f__Peptococcaceae | 1.264453e-03 | 1.169734e-03 |
| f__Elusimicrobiaceae | 1.261359e-03 | 4.278766e-03 |
| f__Burkholderiaceae_A | 9.378374e-04 | 2.509149e-03 |
| f__CAG-508 | 9.213532e-04 | 4.996540e-03 |
| f__Coprobacteraceae | 9.079215e-04 | 1.527339e-03 |
| f__Shewanellaceae | 8.297368e-04 | 2.690699e-03 |
| f__Coprobacillaceae | 7.318328e-04 | 1.542562e-03 |
| f__Sedimentibacteraceae | 6.927406e-04 | 1.016728e-03 |
| f__Xanthobacteraceae | 6.440180e-04 | 2.407832e-03 |
| f__UBA1820 | 5.396558e-04 | 9.137754e-04 |
| f__GCF-1484045 | 4.480219e-04 | 2.494481e-03 |
| f__CALVMC01 | 3.833973e-04 | 1.889124e-03 |
| f__Chlamydiaceae | 3.250519e-04 | 8.432063e-04 |
| f__Borkfalkiaceae | 3.144307e-04 | 5.804720e-04 |
| f__UBA7702 | 2.807538e-04 | 6.721141e-04 |
| f__Eubacteriaceae | 2.693395e-04 | 4.861755e-04 |
| f__UBA3700 | 1.657496e-04 | 9.228548e-04 |
| f__CALYAR01 | 1.366137e-04 | 2.325915e-04 |
| f__Enterococcaceae | 1.029579e-04 | 5.732451e-04 |
| f__UBA660 | 2.552412e-05 | 7.936623e-05 |
family_arrange <- family_summary %>%
group_by(family) %>%
summarise(mean=sum(relabun)) %>%
arrange(-mean) %>%
select(family) %>%
pull()
# Per origin
family_summary %>%
left_join(genome_metadata %>% select(family,phylum) %>% unique(),by=join_by(family==family)) %>%
left_join(sample_metadata,by=join_by(sample==sample)) %>%
filter(family %in% family_arrange[1:20]) %>%
mutate(family=factor(family,levels=rev(family_arrange[1:20]))) %>%
filter(relabun > 0) %>%
ggplot(aes(x=relabun, y=family, group=family, color=phylum)) +
scale_color_manual(values=phylum_colors[-8]) +
geom_jitter(alpha=0.5) +
facet_grid(.~environment)+
theme_minimal() +
labs(y="Family", x="Relative abundance", color="Phylum")5.2.2 Genus
genus_summary <- genome_counts_filt %>%
mutate_at(vars(-genome),~./sum(.)) %>% #apply TSS nornalisation
pivot_longer(-genome, names_to = "sample", values_to = "count") %>% #reduce to minimum number of columns
left_join(sample_metadata, by = join_by(sample == sample)) %>% #append sample metadata
left_join(genome_metadata, by = join_by(genome == genome)) %>% #append genome metadata
group_by(sample,phylum,genus) %>%
summarise(relabun=sum(count)) %>%
filter(genus != "g__") %>%
mutate(genus= sub("^g__", "", genus))
genus_summary_sort <- genus_summary %>%
group_by(genus) %>%
summarise(mean=mean(relabun, na.rm=T),sd=sd(relabun, na.rm=T)) %>%
arrange(-mean)
genus_summary_sort %>%
tt()| genus | mean | sd |
|---|---|---|
| Bacteroides | 2.676340e-01 | 1.399196e-01 |
| Parabacteroides | 6.376349e-02 | 3.960345e-02 |
| Mucinivorans | 6.085416e-02 | 4.344629e-02 |
| Aeromonas | 3.216280e-02 | 5.116161e-02 |
| Mycoplasma_L | 2.602922e-02 | 8.972179e-02 |
| Akkermansia | 2.440550e-02 | 3.614255e-02 |
| Odoribacter | 2.389115e-02 | 2.235810e-02 |
| JADFUS01 | 2.216792e-02 | 1.316718e-02 |
| Hafnia | 1.922885e-02 | 9.188555e-02 |
| UBA866 | 1.817084e-02 | 2.179441e-02 |
| Alistipes | 1.625622e-02 | 1.344232e-02 |
| Plesiomonas | 1.460621e-02 | 3.266225e-02 |
| Parabacteroides_B | 1.344298e-02 | 1.263954e-02 |
| Acinetobacter | 1.342615e-02 | 2.724203e-02 |
| Cetobacterium | 1.241520e-02 | 2.123151e-02 |
| Dielma | 1.189375e-02 | 1.483388e-02 |
| Clostridium | 1.178483e-02 | 1.804656e-02 |
| 14-2 | 9.530791e-03 | 2.077519e-02 |
| Bilophila | 9.443387e-03 | 1.270499e-02 |
| CAJGBR01 | 9.261016e-03 | 8.562777e-03 |
| Angelakisella | 7.718052e-03 | 7.686128e-03 |
| Clostridium_Q | 7.535231e-03 | 8.628377e-03 |
| JAIHAL01 | 7.428449e-03 | 1.475536e-02 |
| Gallibacteroides | 7.109525e-03 | 8.651652e-03 |
| Bacteroides_G | 5.906571e-03 | 6.736493e-03 |
| Hydrogenoanaerobacterium | 5.795122e-03 | 6.095362e-03 |
| Buttiauxella | 5.526548e-03 | 1.517479e-02 |
| SZUA-378 | 5.304805e-03 | 1.559558e-02 |
| Malacoplasma | 5.193336e-03 | 1.101657e-02 |
| HGM05232 | 5.091676e-03 | 6.107022e-03 |
| Hungatella_A | 4.823985e-03 | 5.525123e-03 |
| Anaerotruncus | 4.430928e-03 | 4.607282e-03 |
| Pseudoflavonifractor | 3.911764e-03 | 4.052227e-03 |
| Alistipes_A | 3.867619e-03 | 3.658744e-03 |
| Intestinimonas | 3.801876e-03 | 3.660942e-03 |
| Tidjanibacter | 3.641420e-03 | 3.113585e-03 |
| Anaerovorax | 3.457110e-03 | 7.930141e-03 |
| Anaerorhabdus | 3.342681e-03 | 4.665953e-03 |
| Paraclostridium | 3.303535e-03 | 1.632282e-02 |
| Gallalistipes | 2.764951e-03 | 2.526439e-03 |
| Avirikenella | 2.703337e-03 | 4.073629e-03 |
| Mobilisporobacter | 2.643797e-03 | 4.233095e-03 |
| UMGS1251 | 2.623868e-03 | 4.428322e-03 |
| RGIG3102 | 2.550546e-03 | 4.796159e-03 |
| Egerieousia | 2.488889e-03 | 4.069053e-03 |
| JAGAJR01 | 2.433883e-03 | 5.478338e-03 |
| Craterilacuibacter | 2.083279e-03 | 9.013217e-03 |
| Copranaerobaculum | 2.066120e-03 | 8.740585e-03 |
| UMGS1202 | 1.928935e-03 | 2.061976e-03 |
| Sarcina | 1.883573e-03 | 3.313599e-03 |
| JAAYQI01 | 1.821441e-03 | 2.177416e-03 |
| Amedibacillus | 1.771861e-03 | 2.511258e-03 |
| JAHHTP01 | 1.702809e-03 | 2.122800e-03 |
| Rikenella | 1.556573e-03 | 2.583114e-03 |
| Romboutsia_D | 1.554865e-03 | 3.682587e-03 |
| Evtepia | 1.531626e-03 | 1.774639e-03 |
| Ruthenibacterium | 1.530835e-03 | 2.751232e-03 |
| Deefgea | 1.502709e-03 | 3.412014e-03 |
| Intestinibacillus | 1.498170e-03 | 1.772211e-03 |
| Budvicia | 1.431037e-03 | 6.773380e-03 |
| Butyricimonas | 1.422311e-03 | 1.973337e-03 |
| Pseudomonas_E | 1.420060e-03 | 2.808340e-03 |
| JAGNZR01 | 1.273646e-03 | 4.170041e-03 |
| Phocea | 1.209038e-03 | 2.372714e-03 |
| RGIG4140 | 1.207336e-03 | 6.396700e-03 |
| Negativibacillus | 1.182472e-03 | 1.519004e-03 |
| WRKB01 | 1.173050e-03 | 2.875486e-03 |
| Spyradomonas | 1.153313e-03 | 1.963346e-03 |
| Aminipila | 1.114705e-03 | 2.324044e-03 |
| Romboutsia_A | 1.070399e-03 | 1.851798e-03 |
| Serratia_A | 1.045777e-03 | 3.540183e-03 |
| CAKVBE01 | 1.027988e-03 | 3.204532e-03 |
| JAEZVV01 | 9.378374e-04 | 2.509149e-03 |
| RGIG8482 | 9.213532e-04 | 4.996540e-03 |
| Coprobacter | 9.079215e-04 | 1.527339e-03 |
| RGIG7389 | 9.070330e-04 | 1.099182e-03 |
| Massiliimalia | 8.310581e-04 | 1.432050e-03 |
| Shewanella | 8.297368e-04 | 2.690699e-03 |
| UBA7488 | 8.270131e-04 | 1.824546e-03 |
| Robinsoniella | 7.608379e-04 | 1.761894e-03 |
| Coprobacillus | 7.318328e-04 | 1.542562e-03 |
| Bacilliculturomica | 7.288853e-04 | 1.183076e-03 |
| Kluyvera | 7.218591e-04 | 3.082164e-03 |
| JAJBUQ01 | 6.689051e-04 | 1.230310e-03 |
| IOR16 | 6.685867e-04 | 9.975667e-04 |
| UBA1174 | 6.599272e-04 | 3.520933e-03 |
| Bradyrhizobium | 6.440180e-04 | 2.407832e-03 |
| HGM16780 | 6.169676e-04 | 2.571909e-03 |
| MGBC133411 | 5.654305e-04 | 9.653080e-04 |
| Amedibacterium | 5.586566e-04 | 2.772281e-03 |
| Citrobacter | 4.794230e-04 | 1.553079e-03 |
| Anaerotignum | 4.725340e-04 | 1.010493e-03 |
| Muricomes | 4.633015e-04 | 6.762865e-04 |
| Fimivivens | 4.584178e-04 | 6.442620e-04 |
| 51-20 | 3.751337e-04 | 2.088656e-03 |
| JAGPHI01 | 3.353114e-04 | 7.138362e-04 |
| UBA1794 | 3.283644e-04 | 5.787967e-04 |
| Yersinia | 3.213296e-04 | 1.133201e-03 |
| Longicatena | 3.101858e-04 | 1.727042e-03 |
| Massilioclostridium | 2.871724e-04 | 6.480957e-04 |
| Cryptoclostridium | 2.807538e-04 | 6.721141e-04 |
| CALXSC01 | 2.509121e-04 | 7.682134e-04 |
| Hespellia | 2.508300e-04 | 4.781272e-04 |
| Dysosmobacter | 2.451443e-04 | 4.863795e-04 |
| Scatenecus | 2.189717e-04 | 1.074567e-03 |
| Faecalimonas | 2.166638e-04 | 4.418007e-04 |
| CAZU01 | 1.870860e-04 | 1.041651e-03 |
| SIG603 | 1.481655e-04 | 2.720693e-04 |
| Lactonifactor | 1.397483e-04 | 5.021416e-04 |
| Enterococcus | 1.029579e-04 | 5.732451e-04 |
| MGBC107952 | 2.552412e-05 | 7.936623e-05 |
genus_arrange <- genus_summary %>%
group_by(genus) %>%
summarise(mean=sum(relabun)) %>%
filter(genus != "g__")%>%
arrange(-mean) %>%
select(genus) %>%
mutate(genus= sub("^g__", "", genus)) %>%
pull()
#Per pond
genus_summary %>%
left_join(sample_metadata,by=join_by(sample==sample)) %>%
mutate(genus=factor(genus, levels=rev(genus_summary_sort %>% pull(genus)))) %>%
filter(relabun > 0) %>%
ggplot(aes(x=relabun, y=genus, group=genus, color=phylum)) +
scale_color_manual(values=phylum_colors) +
geom_jitter(alpha=0.5) +
facet_grid(.~environment)+
theme_minimal() +
labs(y="Family", x="Relative abundance", color="Phylum")